Counts the number of datapoints in the criterion availibe at each time interval.
Counts the number of datapoints in the criterion availibe at each time interval. ## by Age : ELSA
Transparent blue lines represent observed trajectories. A random sample was selected from the study’s data to avoid overplotting. Solid red line represents the fixed effects of the intercept and slope that are quantified in the equation in the top right corner.
The legend is the same as in the plot of observed trajectories. This is the same model (using TIME IN STUDY to predict the outcome), however in this graph the trajectories are re-distributed over a different metric of time: Age in years at the time of the interview.
The legend is the same as in the plots above. Semi-transparent blue lines represent the model prediction for each individual, computed from the estimated unique slopes and variances.
The legend is the same as in the plots above. Semi-transparent blue lines represent the model prediction for each individual, computed from the estimated unique slopes and variances.This is the same model as above, only the trajectories are re-distributed over a different metric of time: Age in years at the time of the interview.
\({y_{ti}} = {\beta _{0i}} + {\beta _{1i}}Tim{e_{ti}} + {\varepsilon _{ti}}\\ \\ {\beta _{0i}} = {\gamma _{0.0}} + {\gamma _{0.1}}SE{X_i} + {\gamma _{0.2}}AG{E_i} + {\gamma _{0.3}}E{D_i} + {\gamma _{0.4}}SMOKE{D_i} + {\gamma _{0.5}}CH{F_i} + {\gamma _{0.6}}M{I_i} + {\gamma _{0.7}}ST{K_i} + {\gamma _{0.7}}HP{N_i} + \\ + {\gamma _{0.8}}D{M_i} + {\gamma _{0.9}}HTND{M_i} + {\gamma _{0.11}}AGE\_SE{X_i} + {\gamma _{0.12}}AGE\_HT{N_i} + {\gamma _{0.13}}AGE\_D{M_i} + {\gamma _{0.14}}SEX\_HT{N_i} + {\gamma _{0.15}}SEX\_D{M_i} + {u_{0i}}\\ \\ {\beta _{1i}} = {\gamma _{1.0}} + {\gamma _{1.1}}SE{X_i} + {\gamma _{1.2}}AG{E_i} + {\gamma _{1.3}}E{D_i} + {\gamma _{1.4}}SMOKE{D_i} + {\gamma _{1.5}}CH{F_i} + {\gamma _{1.6}}M{I_i} + {\gamma _{1.7}}ST{K_i} + {\gamma _{1.7}}HP{N_i} + \\ + {\gamma _{1.8}}D{M_i} + {\gamma _{1.9}}HTND{M_i} + {\gamma _{1.11}}AGE\_SE{X_i} + {\gamma _{1.12}}AGE\_HT{N_i} + {\gamma _{1.13}}AGE\_D{M_i} + {\gamma _{1.14}}SEX\_HT{N_i} + {\gamma _{1.15}}SEX\_D{M_i} + {u_{1i}}\\\)